Table: azure_compute_virtual_machine_metric_cpu_utilization_daily - Query Azure Compute Virtual Machines using SQL

Azure Compute is a service within Microsoft Azure that offers scalable and secure virtual machines. These virtual machines provide the power to support large-scale, mission-critical applications. They allow users to deploy a wide range of computing solutions in an agile manner.

Table Usage Guide

The azure_compute_virtual_machine_metric_cpu_utilization_daily table provides insights into the daily CPU utilization of Azure Compute Virtual Machines. As a system administrator or DevOps engineer, explore VM-specific CPU utilization details through this table to identify resource usage patterns and potential performance bottlenecks. Utilize it to monitor and optimize the performance of your Azure Compute resources effectively.

Examples

Basic info

Explore the performance metrics of Azure virtual machines on a daily basis to gain insights into CPU utilization trends. This can help identify instances of resource overload or inefficiency, assisting in better resource management and planning.

select
  name,
  timestamp,
  minimum,
  maximum,
  average,
  sample_count
from
  azure_compute_virtual_machine_metric_cpu_utilization_daily
order by
  name,
  timestamp;

select
  name,
  timestamp,
  minimum,
  maximum,
  average,
  sample_count
from
  azure_compute_virtual_machine_metric_cpu_utilization_daily
order by
  name,
  timestamp;

CPU Over 80% average

This example helps to pinpoint specific instances where the average CPU utilization of Azure virtual machines exceeds 80%. It's useful in identifying potential performance issues and ensuring efficient resource allocation.

select
  name,
  timestamp,
  round(minimum :: numeric, 2) as min_cpu,
  round(maximum :: numeric, 2) as max_cpu,
  round(average :: numeric, 2) as avg_cpu,
  sample_count
from
  azure_compute_virtual_machine_metric_cpu_utilization_daily
where
  average > 80
order by
  name,
  timestamp;

select
  name,
  timestamp,
  round(minimum, 2) as min_cpu,
  round(maximum, 2) as max_cpu,
  round(average, 2) as avg_cpu,
  sample_count
from
  azure_compute_virtual_machine_metric_cpu_utilization_daily
where
  average > 80
order by
  name,
  timestamp;

Schema for azure_compute_virtual_machine_metric_cpu_utilization_daily

Name	Type	Operators	Description
_ctx	jsonb		Steampipe context in JSON form.
average	double precision		The average of the metric values that correspond to the data point.
cloud_environment	text		The Azure Cloud Environment.
maximum	double precision		The maximum metric value for the data point.
minimum	double precision		The minimum metric value for the data point.
name	text		The name of the virtual machine.
resource_group	text		The resource group which holds this resource.
sample_count	double precision		The number of metric values that contributed to the aggregate value of this data point.
sp_connection_name	text	=, !=, ~~, ~~, !~~, !~~	Steampipe connection name.
sp_ctx	jsonb		Steampipe context in JSON form.
subscription_id	text	=, !=, ~~, ~~, !~~, !~~	The Azure Subscription ID in which the resource is located.
sum	double precision		The sum of the metric values for the data point.
timestamp	timestamp with time zone		The time stamp used for the data point.
unit	text		The units in which the metric value is reported.

Export

This table is available as a standalone Exporter CLI. Steampipe exporters are stand-alone binaries that allow you to extract data using Steampipe plugins without a database.

You can download the tarball for your platform from the Releases page, but it is simplest to install them with the steampipe_export_installer.sh script:

/bin/sh -c "$(curl -fsSL https://steampipe.io/install/export.sh)" -- azure

You can pass the configuration to the command with the --config argument:

steampipe_export_azure --config '<your_config>' azure_compute_virtual_machine_metric_cpu_utilization_daily